package com.lyx.langchain4j.ai;


import com.lyx.langchain4j.ai.Tools.InterviewQuestionTool;
import dev.langchain4j.mcp.McpToolProvider;
import dev.langchain4j.memory.ChatMemory;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.chat.ChatModel;
import dev.langchain4j.model.chat.StreamingChatModel;
import dev.langchain4j.rag.content.retriever.ContentRetriever;
import dev.langchain4j.service.AiServices;
import jakarta.annotation.Resource;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class aiCodeHelperServiceFactory {

    @Resource
    private ChatModel myQwenChatModel;
    @Resource
    private ContentRetriever contentRetriever;
    @Resource
    private McpToolProvider mcpToolProvider;
    @Resource
    private StreamingChatModel qwenStreamingChatModel;

    @Bean
    public aiCodeHelperService aiCodeHelperService() {
        //回话记忆
        ChatMemory chatMemory = MessageWindowChatMemory.withMaxMessages(10);
        //构造AI service
        aiCodeHelperService aiCodeHelperService = AiServices.builder(aiCodeHelperService.class)
                .chatModel(myQwenChatModel)
                .streamingChatModel(qwenStreamingChatModel)//流式输出
                .chatMemory(chatMemory)//会话记忆
                .chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(10))//会话独立存储
                .contentRetriever(contentRetriever)//rag内容检索
                .tools(new InterviewQuestionTool())//工具
                .toolProvider(mcpToolProvider)//mcp工具
                .build();
        return aiCodeHelperService;

    }
}
